rlcm {lca} | R Documentation |
Generates independent random instances of a Latent Class Model with given parameters.
rlcm(n, theta, eta, varnames = NULL, lc = TRUE)
n |
number of independent observations to generate. |
theta |
numeric vector of latent class proportions. |
eta |
other parameters in array of class lcm.params |
varnames |
optional character vector containing names of the items. |
lc |
logical - should output include information on latent class membership? |
The n
individual responses are independent observations from a latent
class model, with H
latent classes; H
is infered from the length
of theta
. Each individual is randomly assigned a latent class h
with probability theta[h]
.
Then for each individual, conditional on their membership of class h
,
the probability of responding k
to item j
is eta[h,j,k]
,
independently of their other responses.
rlcm
tabulates the results.
An object of class freq.table
containing the results. The first J
columns contain the item response pattern; if lc = TRUE
the next column
will contain the latent class. The last column contains the counts.
Robin Evans
Goodman, L.A. (1974) - Exploratory Latent Structure Analysis Using Both Identifiable and Unidentifiable Models, Biometrika, Vol. 61 (2), pp 215-331.
theta = c(0.4, 0.6) eta = c(0.9,0.2,0.9,0.2,0.9,0.2) eta = array(c(eta,1-eta), c(2,3,2)) set.seed(123) rlcm(1000, theta, eta, lc=FALSE)